On the origin of central abundance drops in the intracluster medium of galaxy groups and clusters
Bibliographic record
Abstract
A central drop of ICM Fe abundance has been observed in several cool-core clusters. It has been proposed that this abundance drop may be due, at least partially, to the depletion of Fe into dust grains in the central, high-density regions. According to this scenario, noble gas elements such as Ar and Ne are not expected to be depleted into dust, and therefore should not show any drop, but follow the general increase of metal abundance towards the centre. In this work, we test this scenario by measuring with Chandra data the radial profiles of Ar and Ne in a sample of 12 groups and clusters where a central drop in Fe abundance has been detected. We confirm the presence of the Fe drop in 10 out of 12 clusters at more than 2σ c.l., and 4 Ar drops with similar significance. We also find 4 Ne drops, with the caveat that Ne abundance measurement from CCD spectra suffers from systematics not completely under control. Our results are consistent with an abundance drop common to the three elements. When comparing the profiles, we find that, on average, the abundance profiles of Ar and Ne are significantly higher than Fe and steeper towards the centre, while they all gradually become consistent with solar composition at r ≥ 0.05r500. We also check that Si and S profiles are mostly consistent with Fe. This result confirms a scenario in which some fraction of Fe is depleted into dust grains in the inner regions, although the global central abundance drop is mostly due to mechanical processes, like the displacement of metal-rich ICM from the very centre to larger radii by AGN-driven feedback. Finally, we report the detection of an Fe drop in the cluster MACSJ1423.8+2404 at |$z$| = 0.543, showing that this feature appears early on in cool-core clusters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".